This session introduces AI from a practitioner’s perspective. We’ll start with the foundations: how modern machine learning models work, the role of training data, and the lifecycle of model development and deployment. From there, we’ll look at practical use cases for developers, including code generation, natural language interfaces, image processing, and anomaly detection. We’ll also examine common pitfalls such as data leakage, prompt injection, adversarial inputs, and model bias, with concrete examples of how developers can defend against them. Attendees will leave with a clear understanding of AI fundamentals, hands-on considerations for integration into applications, and a roadmap for building AI features securely and responsibly.-